code: def step(self, state, y=None):
      self.t += 1
  
      # Proposal distribution
      pyro.sample(
          "z_{}".format(self.t),
          dist.Normal(
              state["z"].matmul(self.model.A), torch.tensor([2.0, 2.0])
          ).to_event(1),
      )
  
imports: import pytest
  import torch
  import pyro
  import pyro.distributions
  import pyro.poutine
  from pyro.infer import SMCFilter
  from pyro.infer.smcfilter import _systematic_sample
  from tests.common import assert_close
label_desc: Use image node_id 3 for calling the HarmonicGuide obj's underlying member method code with example usage: obj.step(state, y) without return types